Installation
BICAM is available on PyPI and can be installed using pip.
Requirements
Python 3.8 or higher
12GB+ free disk space (for the complete dataset)
Internet connection for downloads
Basic Installation
Install BICAM using pip:
pip install bicam
For the latest development version:
pip install git+https://github.com/bicam-data/bicam.git
Using uv (Recommended)
If you use uv for Python package management:
uv pip install bicam
Using conda
BICAM is not yet available on conda-forge, but you can install it in a conda environment:
conda create -n bicam python=3.11
conda activate bicam
pip install bicam
Verification
After installation, verify that BICAM is working:
bicam --version
bicam list
You should see the version number and a list of available datasets.
Configuration
BICAM uses sensible defaults and requires no configuration. However, you can customize:
Cache Directory
By default, BICAM stores downloaded data in the following locations:
Platform |
Default Cache Directory |
Windows |
%LOCALAPPDATA%\bicam |
macOS/Linux |
~/.bicam |
To use a custom cache directory:
export BICAM_DATA=/path/to/custom/cache
bicam download bills
Environment Variables
Variable |
Description |
|---|---|
BICAM_DATA |
Custom cache directory |
BICAM_LOG_LEVEL |
Logging level (DEBUG, INFO, WARNING, ERROR) |
Troubleshooting
Permission Errors If you encounter permission errors on Windows, try running as administrator or use a different cache directory.
Disk Space Ensure you have sufficient disk space. The complete dataset requires ~12GB, and requires intermediate storage when downloading the data.
Network Issues BICAM requires internet access to download datasets. Check your firewall settings if downloads fail.
Python Version BICAM requires Python 3.8+. Check your version with:
python --version